{"id":"W4312178128","doi":"10.18280/ria.360513","title":"Shadow Detection and Elimination Technique for Vehicle Detection","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Vehicle License Plate Recognition","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shadow (psychology); Computer vision; Artificial intelligence; Computer science; Object detection; Segmentation; Image warping; Similarity (geometry); Image processing; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003214607,0.000109818,0.0001021078,0.0001559446,0.0003836406,0.00004299172,0.00007281548,0.00006112523,0.00006760035],"category_scores_gemma":[0.00003847575,0.0001424817,0.0000462197,0.000301331,0.00002490586,0.0001482558,0.00003312776,0.0001932908,0.00001866398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001456469,"about_ca_system_score_gemma":0.000005684547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001147057,"about_ca_topic_score_gemma":0.00003215097,"domain_scores_codex":[0.9992332,0.00003163236,0.0002296757,0.0002141243,0.00009509434,0.0001962994],"domain_scores_gemma":[0.9996323,0.00009651871,0.00004206078,0.0001348281,0.00005233837,0.0000419369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002245947,0.00002197343,0.000008560753,0.00008251343,0.00000767497,0.000001110138,0.0002678221,0.09769445,0.6540945,0.0001381269,0.00001138025,0.2476495],"study_design_scores_gemma":[0.00002432185,0.00009130365,0.00002930411,0.000007168537,0.000007931536,0.00003674707,0.0002909449,0.5074763,0.4898237,0.0008114831,0.001307076,0.00009370786],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2465531,0.0001213866,0.75157,0.00006517655,0.00030422,0.000663488,0.00001482345,0.0002748705,0.000432949],"genre_scores_gemma":[0.9980729,0.00004109809,0.0008039835,0.00001806369,0.00006772668,0.0008705084,0.00001268884,0.0000344166,0.00007862709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7515198,"threshold_uncertainty_score":0.5810236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02125936294131046,"score_gpt":0.2313973465863917,"score_spread":0.2101379836450812,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}